How to integrate Zep MCP with CrewAI

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Introduction

This guide walks you through connecting Zep to CrewAI using the Composio tool router. By the end, you'll have a working Zep agent that can store a memory about today's meeting, retrieve all memories tagged urgent, summarize knowledge about client preferences through natural language commands.

This guide will help you understand how to give your CrewAI agent real control over a Zep account through Composio's Zep MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

TL;DR

Here's what you'll learn:
  • Get a Composio API key and configure your Zep connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Zep
  • Build a conversational loop where your agent can execute Zep operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

What is the Zep MCP server, and what's possible with it?

The Zep MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Zep account. It provides structured and secure access so your agent can perform Zep operations on your behalf.

Supported Tools & Triggers

Tools
Add Fact TripleTool to add a manually specified fact triple (subject-predicate-object) to the Zep knowledge graph.
Add Session MemoryTool to add memory messages to a specified Zep session.
Add Thread MessagesTool to add chat messages to a thread in Zep and ingest them into the user knowledge graph.
Clone GraphTool to clone a user or group graph with new identifiers in Zep.
Create GraphTool to create a new graph by adding data to Zep.
Create GroupTool to create a new group in Zep for multi-user graph management.
Create SessionTool to create a new session in Zep for storing conversation memory.
Create ThreadTool to create a new thread in Zep for a specific user.
Create UserTool to create a new user in Zep with properties like user_id, email, and metadata.
Delete GraphTool to delete a graph from Zep.
Delete GroupTool to delete a group from Zep.
Delete Session MemoryTool to delete a session and its memory from Zep.
Delete ThreadTool to delete a thread and its messages from Zep.
Delete UserTool to delete a user and all associated threads and artifacts from Zep.
Get Edge by UUIDTool to retrieve a specific edge by its UUID from the Zep knowledge graph.
Get Graph by IDTool to retrieve a graph by its unique identifier from Zep.
Get Group by IDTool to retrieve a group by ID from Zep.
Get Node Entity EdgesTool to retrieve all entity edges for a specific node in the Zep knowledge graph.
Get Project InfoTool to retrieve project information based on the provided API key.
Get Session by IDTool to retrieve a session by its unique identifier from Zep.
Get Session MemoryTool to retrieve memory for a given session including relevant facts and entities.
Get Session Message by UUIDTool to retrieve a specific message by UUID from a Zep session.
Get Session MessagesTool to retrieve messages for a given session from Zep.
Get Task StatusTool to check the status of asynchronous operations in Zep.
Get Thread MessagesTool to retrieve conversation history for a specific thread from Zep.
Get Thread User ContextTool to retrieve the most relevant user context from the user graph based on thread messages.
Get User by IDTool to retrieve a user by their user ID from Zep.
Get User NodeTool to retrieve a user's graph node and summary from Zep.
Get User NodesTool to retrieve all nodes for a specific user from their graph in Zep.
Get User SessionsTool to retrieve all sessions for a user from Zep.
Get User ThreadsTool to retrieve all threads for a specific user from Zep.
Graph SearchTool to perform hybrid graph search combining semantic similarity and BM25 full-text search across the Zep knowledge graph.
List GraphsTool to retrieve all graphs from Zep with pagination support.
List Groups OrderedTool to retrieve all groups from Zep with pagination support.
List Sessions OrderedTool to retrieve all sessions from Zep with pagination and ordering support.
List ThreadsTool to retrieve all threads from Zep with pagination support.
List Users OrderedTool to retrieve all users from Zep with pagination support.
List All ThreadsTool to list all threads with pagination and ordering support.
Update GraphTool to update graph information in Zep including name and description.
Update GroupTool to update group information in Zep including name, description, and fact rating instructions.
Update MessageTool to update a message in a Zep thread.
Update Session MetadataTool to update session metadata in Zep.
Update UserTool to update an existing user's information in Zep including email, metadata, and ontology settings.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Zep connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.

Install dependencies

bash
pip install composio crewai crewai-tools[mcp] python-dotenv
What's happening:
  • composio connects your agent to Zep via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools[mcp] includes MCP helpers
  • python-dotenv loads environment variables from .env

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model

Import dependencies

python
import os
from composio import Composio
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
import dotenv

dotenv.load_dotenv()

COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Zep MCP URL

Create a Composio Tool Router session for Zep

python
composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["zep"])

url = session.mcp.url
What's happening:
  • You create a Zep only session through Composio
  • Composio returns an MCP HTTP URL that exposes Zep tools

Initialize the MCP Server

python
server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users search the internet effectively",
        backstory="You are a helpful assistant with access to search tools.",
        tools=tools,
        verbose=False,
        max_iter=10,
    )
What's Happening:
  • Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication.
  • MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format.
  • Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools.
  • Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops.
  • Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries.

Create a CLI Chatloop and define the Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")

conversation_context = ""

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Conversation history:\n{conversation_context}\n\n"
            f"Current request: {user_input}"
        ),
        expected_output="A helpful response addressing the user's request",
        agent=agent,
    )

    crew = Crew(agents=[agent], tasks=[task], verbose=False)
    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's Happening:
  • Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable.
  • Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean.
  • Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses.
  • Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context.
  • Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response.
  • Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity.

Complete Code

Here's the complete code to get you started with Zep and CrewAI:

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter
from composio import Composio
from dotenv import load_dotenv
import os

load_dotenv()

GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_API_KEY is not set in the environment.")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment.")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment.")

# Initialize Composio and create a session
composio = Composio(api_key=COMPOSIO_API_KEY)
session = composio.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["zep"],
)
url = session.mcp.url

# Configure LLM
llm = LLM(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY"),
)

server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users with internet searches",
        backstory="You are an expert assistant with access to Composio Search tools.",
        tools=tools,
        llm=llm,
        verbose=False,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end.\n")

    conversation_context = ""

    while True:
        user_input = input("You: ").strip()

        if user_input.lower() in ["exit", "quit", "bye"]:
            print("\nGoodbye!")
            break

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Conversation history:\n{conversation_context}\n\n"
                f"Current request: {user_input}"
            ),
            expected_output="A helpful response addressing the user's request",
            agent=agent,
        )

        crew = Crew(agents=[agent], tasks=[task], verbose=False)
        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

Conclusion

You now have a CrewAI agent connected to Zep through Composio's Tool Router. The agent can perform Zep operations through natural language commands.

Next steps:

  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations

How to build Zep MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Zep MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Zep MCP with Claude Agent SDK

Google ADK

Google ADK

Use Zep MCP with Google ADK

LangChain

LangChain

Use Zep MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Zep MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Zep MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Zep MCP with LlamaIndex

Claude Code

Claude Code

Use Zep MCP with Claude Code

Codex

Codex

Use Zep MCP with Codex

FAQ

What are the differences in Tool Router MCP and Zep MCP?

With a standalone Zep MCP server, the agents and LLMs can only access a fixed set of Zep tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Zep and many other apps based on the task at hand, all through a single MCP endpoint.

Can I use Tool Router MCP with CrewAI?

Yes, you can. CrewAI fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Zep tools.

Can I manage the permissions and scopes for Zep while using Tool Router?

Yes, absolutely. You can configure which Zep scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Zep data and credentials are handled as safely as possible.

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